Integration Specifications
This article will help you learn about how Daasity replicates data from Thankful, limitations to the data we can extract and where the data is stored in the Thankful schema
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This article will help you learn about how Daasity replicates data from Thankful, limitations to the data we can extract and where the data is stored in the Thankful schema
Last updated
Was this helpful?
Thankful is an A.I.-powered customer service software for retail and e-commerce businesses, using Natural Language Processing (NLP) to understand what customers want and deliver the service they need.
This document provides context on what kind of data is being gathered through this extractor, which endpoints that data is coming from, and how the extracted tables relate to each other.
This integration is available for:
Enterprise
The Daasity Thankful extractor is built based on this . The following endpoints are used by Daasity to replicate data from Thankful:
The Daasity Thankful extractor creates these tables using the endpoints and replication methods listed. The data is mapped from source API endpoint to the table based on the mapping logic outlined in each table.
Update Method: UPSERT
Table Name: [thankful.action_names
]
id
action_id
name
action_name
Daasity: current timestamp
created_at
Daasity: account_id
_account_id
Daasity: MD5(id)
__sync_key
Daasity: timestamp when loaded into DB
loaded_at
Update Method: UPSERT
Table Name: [thankful.top_actions
]
MD5(TopActions::ID + 1.days.ago.utc)
top_action_id
TopActions::ID
action_id
TopActions::Capture
capture_count
TopActions::Resolve
resolve_count
TopActions::Pending
pending_count
TopActions::Transfer
transfer_count
TopActions::Handoff
handoff_count
TopActions::Skip
skip_count
TopActions::Enabled
is_active
Daasity: 1.days.ago.utc
created_at
Daasity: account_id
_account_id
Daasity: MD5(TopActions::ID + 1.days.ago.utc)
__sync_key
Daasity: timestamp when loaded into DB
loaded_at
Update Method: UPSERT
Table Name: [thankful.handoff_metrics
]
MD5(ActionID + type::ID + 1.days.ago.utc)
transfer_handoff_metric_id
ActionID
action_id
type::ID
type_id
type::Cause
handoff_cause
type::ActionHandoffCount
handoff_count
Daasity: 1.days.ago.utc
created_at
Daasity: account_id
_account_id
Daasity: MD5(ActionID + type::ID + 1.days.ago.utc)
__sync_key
Daasity: timestamp when loaded into DB
__synced_at
Update Method: UPSERT
Table Name: [thankful.recommendations
]
MD5(Recommendations::ActionID + 1.days.ago.utc)
recommendation_id
Recommendations::ActionID
action_id
Recommendations::Impact
recommendation
Daasity: 1.days.ago.utc
created_at
Daasity: account_id
_account_id
Daasity: MD5(Recommendations::ActionID + 1.days.ago.utc)
__sync_key
Daasity: timestamp when loaded into DB
__synced_at
Update Method: UPSERT
Table Name: [thankful.savings
]
savings::Hours
hours_saved
Daasity: 1.days.ago.utc
created_at
Daasity: account_id
_account_id
Daasity: MD5(1.days.ago.utc)
__sync_key
Daasity: timestamp when loaded into DB
__synced_at
Update Method: UPSERT
Table Name: [thankful.ticket_metrics
]
TicketsOverTime::ReceivedTotal
received_count
TicketsOverTime::CapturedTotal
captured_count
TicketsOverTime::TransferredTotal
transferred_count
TicketsOverTime::ResolvedTotal
resolved_count
Daasity: 1.days.ago.utc
created_at
Daasity: account_id
_account_id
Daasity: MD5(1.days.ago.utc)
__sync_key
Daasity: timestamp when loaded into DB
__synced_at
illustrating the different tables and keys to join across tables.
Endpoint:
Endpoint:
Endpoint:
Endpoint:
Endpoint:
Endpoint: